System to manage patient hydration

ABSTRACT

Techniques for predicting fluid responsiveness or fluid unresponsiveness are described. A processor can determine a first prediction of fluid responsiveness or unresponsiveness based on a plethysmograph variability parameter associated with a plethysmograph waveform, and can determine a second prediction of fluid responsiveness or unresponsiveness based on a fluid responsiveness parameter that is associated with an elevation of one or more limbs of the patient. The processor can determine an overall prediction of fluid responsiveness or unresponsiveness based on the first and/or second predictions. Based on overall prediction, the processor can cause administration of fluids and/or termination of administration of fluids.

RELATED APPLICATIONS

The application claims priority to U.S. Provisional Application No.62/755,802, filed Nov. 5, 2018, entitled “System To Manage PatientHydration,” which is hereby incorporated by reference in its entirety.

TECHNICAL FIELD

The present disclosure relates generally to management of patienthydration and assessment of fluids responsiveness.

BACKGROUND

In the management of patients, the decision to administer fluidsconstitutes a common dilemma for physicians. For example, although aparticular patient may be at least partially dehydrated (for example,due to preoperative fasting, sweat loss, urinary excretion, surgicalblood loss, fluid shifts or other pathologic processes), the patient maynot respond favorably to fluid administration (e.g., intravenous (IV)therapy). That is, the patient may not respond to fluid administrationwith an increase in stroke volume.

Accordingly, prior to or during fluid administration, it can bedesirable to predict whether the patient's stroke volume (or, in somecases, cardiac output) will increase upon the fluid administration.Unfortunately, accurate prediction of an increase in stroke volume orcardiac output upon fluid loading, so-called fluid responsiveness, hasproven to be difficult and/or unreliable.

SUMMARY

Techniques for predicting fluid responsiveness or fluid unresponsivenessare described. A processor can determine a first prediction of fluidresponsiveness or unresponsiveness based on a plethysmograph variabilityparameter associated with a plethysmograph waveform, and can determine asecond prediction of fluid responsiveness or unresponsiveness based on afluid responsiveness parameter that is associated with an elevation ofone or more limbs of the patient. The processor can determine an overallprediction of fluid responsiveness or unresponsiveness based on thefirst and/or second predictions. Based on overall prediction, theprocessor can cause administration of fluids and/or termination ofadministration of fluids.

In various embodiments, the system can identify a patient's hydrationstatus based on physiological data associated with a patient. Forexample, in some cases, physiological data can correspond to aplethysmography (pleth) signal detected by a pulse oximetry device.Based on the physiological data, the system can identify a plethvariability parameter that is indicative of the hydration status of thepatient, and can determine the hydration status of the patient based onthe pleth variability parameter. As a non-limiting example, the plethvariability parameter can include a pleth variability index (PVI). Forexample, PVI can be obtained noninvasively, automatically, andcontinuously, and can quantify respiratory induced variations in aperfusion index. PVI can be an indicator of a patient's hydration status(for example, hydrated or dehydrated) and can be presented as anumerical value. In some cases, based on PVI the system can determine ahydration status of the patient.

In some cases, a method of determining fluid responsiveness of a patientincludes receiving a sensor signal corresponding to a non-invasivephysiological sensor. The non-invasive physiological sensor can beconfigured to emit light towards a tissue site of a patient, detect thelight after it has interacted with the tissue site, and generate thesensor signal based at least in part on the detected light. The methodcan further include demodulating the sensor signal to generate aplethysmograph waveform including a plurality of pulses corresponding topulsatile blood flow within the tissue site. The method can furtherinclude determining a plethysmograph variability parameter associatedwith the plethysmograph waveform. The plethysmograph variabilityparameter can quantify variations in the plethysmograph waveform. Themethod can further include determining a first prediction of fluidresponsiveness based at least in part on the plethysmograph variabilityparameter. The method can further include determining a secondprediction of fluid responsiveness based at least in part on a fluidresponsiveness parameter that is associated with an elevation of one ormore limbs of the patient. The method can further include outputting anindication of fluid responsiveness of the patient based at least in parton the first prediction of fluid responsiveness and the secondprediction of fluid responsiveness.

The method of any of the preceding paragraphs and/or any of the methodsdisclosed herein may include any combination of the following steps orfeatures described in this paragraph, among other features describedherein. The plethysmograph variability parameter can correspond to avalue associated with a pleth variability index (PVI). The fluidresponsiveness parameter can include a measure of at least one ofcardiac output, heart rate, or stroke volume. The method can furtherinclude determining a plurality of perfusion parameters based at leastin part on the plethysmograph waveform. A particular perfusion parameterof the plurality of perfusion parameters can be determined based atleast in part on a peak amplitude and a valley amplitude of acorresponding pulse of the plurality of pulses. Said determining theplethysmograph variability parameter can be based at least in part on adifference between a first and second perfusion parameter of theplurality of perfusion parameters relative to the first perfusionparameter of the plurality of perfusion parameters. The indication offluid responsiveness of the patient can be an overall prediction offluid responsiveness of the patient.

The method of any of the preceding paragraphs and/or any of the methodsdisclosed herein may include any combination of the following steps orfeatures described in this paragraph, among other steps or featuresdescribed herein. The method can be performed prior to administrationfluids to the patient. The method can be performed during administrationfluids to the patient. The elevation of the one or more limbs of thepatient can be associated with a passive leg raising (PLR) test. The PLRtest can be performed prior to administration of fluids to the patient.The PLR test can be performed during administration of fluids to thepatient. The method can include performing an action based at least inpart on the indication of the fluid responsiveness. The action caninclude at one of initiating administration of fluids to the patient,terminating the administration of the fluids to the patient, causing adisplay to display an indication of a recommendation for fluidadministration, or causing the display to display an indication of arecommendation for termination of fluid administration. The indicationof fluid responsiveness can indicate a response of stroke volume of thepatient to fluid administration. The method can include determining afirst confidence parameter corresponding to the first prediction offluid responsiveness; and determining a second confidence parametercorresponding to the second prediction of fluid responsiveness. Thefluid responsiveness of the patient can be further based at least inpart on the first confidence parameter and the second confidenceparameter.

In some cases, a system for determining fluid responsiveness of apatient can include a sensor interface and a processor in communicationwith the sensor interface. The sensor interface can be configured toconnect to a non-invasive physiological sensor and to receive a sensorsignal from the non-invasive physiological sensor. The non-invasivephysiological sensor can be configured to emit light towards a tissuesite of a patient, detect the light after it has interacted with thetissue site, and generate the sensor signal based at least in part onthe detected light. The processor can be configured to determine aplethysmograph variability parameter associated with a plethysmographwaveform corresponding to the sensor signal. The plethysmograph waveformcan include a plurality of pulses corresponding to pulsatile blood flowwithin the tissue site. The plethysmograph variability parameter canquantify variations in the plethysmograph waveform. The processor can befurther configured to determine a first prediction of fluidresponsiveness based at least in part on the plethysmograph variabilityparameter. The processor can be further configured to determine a secondprediction of fluid responsiveness based at least in part on a fluidresponsiveness parameter that is associated with an elevation of one ormore limbs of the patient. The processor can be further configured tooutput an indication of fluid responsiveness of the patient based atleast in part on the first prediction of fluid responsiveness and thesecond prediction of fluid responsiveness.

The patient monitoring device of any of the preceding paragraphs and/orany of the patient monitoring devices disclosed herein may include anycombination of the following features described in this paragraph, amongother features described herein. The plethysmograph variabilityparameter can correspond to a value associated with a pleth variabilityindex (PVI). The fluid responsiveness parameter can include a measure ofat least one of cardiac output, heart rate, or stroke volume. Theelevation of the one or more limbs of the patient can be associated witha passive leg raising (PLR) test. The PLR test can be performed prior toadministration of fluids to the patient. The PLR test can be performedduring administration of fluids to the patient. The processor can befurther configured to cause an action based on the fluid responsivenessof the patient, wherein the action can include at least one ofinitiating administration of fluids to the patient, terminating theadministration of the fluids to the patient, causing a display todisplay an indication of a recommendation for fluid administration, orcausing the display to display an indication of a recommendation fortermination of fluid administration. The processor can be furtherconfigured to determine a first confidence parameter corresponding tothe first prediction of fluid responsiveness; and determine a secondconfidence parameter corresponding to the second prediction of fluidresponsiveness. The fluid responsiveness of the patient can be furtherbased at least in part on the first confidence parameter and the secondconfidence parameter.

Any of the features of any of the methods described herein can be usedwith any of the features of any of the other methods described herein.Any of the features of any of the systems, devices, or methodsillustrated in the figures or described herein can be used with any ofthe features of any of the other systems, devices, or methodsillustrated in the figures or described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The following drawings and the associated descriptions are provided toillustrate embodiments of the present disclosure and do not limit thescope of the claims.

FIG. 1 is an example block diagram of a patient monitoring device.

FIG. 2A is a perspective view of an example patient monitoring deviceincluding a hub and the patient monitoring device of FIG. 1.

FIG. 2B illustrates an example hardware block diagram of the hub of FIG.2B.

FIG. 3 illustrates a perspective view of the back of the patientmonitoring device of FIG. 2A.

FIG. 4 illustrates a pleth signal plotted on an intensity axis versus atime axis.

FIG. 5 is a flow diagram illustrative of an embodiment of a routine forassessing or predicting fluid responsiveness.

FIGS. 6A-6C illustrate embodiments of example GUIs that displays examplegraphics for instructing or implementing the PLR test on a patient.

FIG. 7 illustrates an embodiment of an example GUI that displays a fluidadministration recommendation based on the hydration status and/or fluidresponsiveness of the patient.

While the foregoing “Brief Description of the Drawings” referencesgenerally various embodiments of the disclosure, an artisan willrecognize from the disclosure herein that such embodiments are notmutually exclusive. Rather, the artisan would recognize a myriad ofcombinations of some or all of such embodiments.

DETAILED DESCRIPTION

FIG. 1 is an example block diagram of a patient monitoring device 100.The patient monitoring device can include a docked portable patientmonitor 100, which may be referred to herein as the patient monitoringdevice 100. The patient monitoring device 100 may advantageously includean oximeter, co-oximeter, respiratory monitor, depth of sedationmonitor, noninvasive blood pressure monitor, vital signs monitor or thelike, such as those commercially available from Masimo Corporation ofIrvine, Calif., and/or disclosed in U.S. Patent Publication Nos.2002/0140675, 2010/0274099, 2011/0213273, 2012/0226117, 2010/0030040;U.S. Patent Application Ser. Nos. 61/242,792, 61/387,457, 61/645,570,13/554,908 and U.S. Pat. Nos. 6,157,850, 6,334,065, and the like.

The patient monitoring device 100 can include a first processor 104, adisplay 106, and an OEM board 108. The patient monitoring device 100further includes one or more cables 110 and an antenna 112 for wired andwireless communication, respectively.

The OEM board 108 can include an instrument board 114, a core ortechnical board 116, and memory 118. In some cases, the memory 118 caninclude a user interface module 120, a signal processing module 122,instrument configuration parameters 124, and local configurationparameters 126.

The patient monitoring device 100 may communicate with a variety ofnoninvasive and/or minimally invasive sensors 102 such as opticalsensors with light emission and detection circuitry, acoustic sensors,devices that measure blood parameters from a finger prick, cuffs,ventilators, ECG sensors, pulse oximeters, and the like.

One or more of the sensors 102 can be attached to a medical patient. Thesensors 102 can obtain physiological information from a medical patientand transmit this information to the technical board 116 through cables130 or through a wireless connection (not shown). The physiologicalinformation can include one or more physiological parameters or valuesand waveforms corresponding to the physiological parameters.

The technical board 116 can receive physiological information from thesensors 102. The technical board 116 can include a circuit having asecond processor, which may be the same as the first processor 104, andinput ports for receiving the physiological information. The technicalboard 116 can access the signal processing module 122 to process thephysiological information in the second processor. In addition, thetechnical board 116 can include one or more output ports, such as serialports. For example, an RS232, RS423, or autobaud RS232 (serial interfacestandard) port or a universal serial bus (USB) port may be included inthe technical board 116.

The technical board 116 and the signal processing module 122 can includea sensor processing system for the patient monitoring device 100. Insome cases, the sensor processing system generates waveforms fromsignals received from the sensors 102. The sensor processing system mayalso analyze single or multiparameter trends to provide early warningalerts to clinicians prior to an alarm event. In addition, the sensorprocessing system can generate alarms in response to physiologicalparameters exceeding certain safe thresholds.

Example alerts include no communication with the patient monitoringdevice 100, alarm silenced on the patient monitoring device 100,instrument low battery (patient monitoring device 100), transmitter lowbattery, and/or indications of fluid responsiveness. Examplephysiological parameters include SpO₂ levels, high and low SpO₂, highand low PR, HbCO level, HbMET level, pulse rate, perfusion index, signalquality, HbCO, HbMET, PI, and desat index. Additional example alarmsinclude SpO₂ alarms, high and low SpO₂ alarms, high and low PR, HbCOalarms, HbMET alarms, pulse rate alarms, no sensor alarms, sensor offpatient alarms, sensor error, low perfusion index alarm, low signalquality alarm, HbCO alarm, HbMET alarm, PI trend alarm, and desat indexalarm.

The instrument board 114 can receive the waveforms, alerts, alarms, andthe like from the technical board 116. The instrument board 114 caninclude a circuit having a third processor, which may be the same as thefirst processor 104, and input ports for receiving the waveforms,alerts, and alarms from the technical board 116 and output ports forinterfacing with the display 106, a speaker or other device capable ofproducing an audible indication. The instrument board 114 can access theuser interface module 120 to process the waveforms, alerts, and alarmsto provide indications of the waveforms, alerts, alarms or other dataassociated with the physiological parameters monitored by the sensors102. The indications can be displayed on the display 106. In addition oralternatively, the alerts and alarms are audible. The indications,alerts, and alarms can be communicated to end-user devices, for example,through a hospital backbone, a hospital WLAN 16, and/or the Internet.

Additionally, the instrument board 114 and/or the technical board 116may advantageously include one or more processors and controllers,busses, all manner of communication connectivity and electronics,memory, memory readers including EPROM readers, and other electronicsrecognizable to an artisan from the disclosure herein. Each board caninclude substrates for positioning and support, interconnect forcommunications, electronic components including controllers, logicdevices, hardware/software combinations and the like to accomplish thetasks designated above and others.

An artisan will recognize from the disclosure herein that the instrumentboard 114 and/or the technical board 116 may include a large number ofelectronic components organized in a large number of ways.

Because of the versatility needed to process many differentphysiological parameters, the technical board 116 can further include arevision number or other indication of the circuit design andcapabilities of a specific technical board 116.

Likewise, because of the versatility needed to display the processedphysiological parameters for use by many different end users, theinstrument board 114 can further include a revision number or otherindication of the circuit design and capabilities of the specificinstrument board.

Software is also subject to upgrading to increase its capabilities. Thesignal processing module 122 can further include a version number orother indication of the code found in the specific signal processingmodule 122. Likewise, the user interface module 120 can further includea version number or other indication of the code found on the specificuser interface module 120.

Some or all of the serial numbers, the model numbers, and the revisionnumbers of the technical board 116 and the instrument board 114 thatinclude the specific patient monitoring device 100 can be stored in theinstrument configuration parameters 124. Further, the version numbers ofthe signal processing module 122 and the user interface module 120 arestored in the instrument configuration parameters 124. The instrumentconfiguration parameters 124 can further include indications of thephysiological parameters that are enabled, and indications of thephysiological parameters that are capable of being enabled for thepatient monitoring device 100.

The location of the patient monitoring device 100 can affect thesensitivity at which a physiological parameter is monitored. Forexample, a physiological parameter may be monitored with greatersensitivity when the patent monitoring device 100 is located in theneonatal intensive care unit (NICU), OR or surgical ICU than when it islocated in an adult patient's room. In some cases, the location of thepatient monitoring device 100 may affect the availability of the devicefor another patient. For example, a patient monitoring device 100located in the hospital discharge area may be available for anotherpatient, whereas one located in a patient's room may not be availableanytime soon.

The local configuration parameters 126 can include a location of thepatient monitoring device 100 within the facility, an indication ofwhether the device is configured for adult or pediatric monitoring, andthe like.

The sensor 102 can include memory 128. The memory 128 can includeinformation associated with the sensor 102, such as, but not limited toa sensor type, a sensor model number, a sensor revision number, a sensorserial number, and the like.

The patient monitoring device 100 can include a Radical-7® Rainbow SETPulse Oximeter by Masimo Corporation, Irvine, Calif. The OEM board 108can be produced by Masimo Corporation, Irvine, Calif. and used by othersto produce patient monitoring devices.

FIG. 2A illustrates a perspective view of an example patient monitoringdevice, such as a medical monitoring hub with the docked portablepatient monitoring device 100, the combination of which may also bereferred to herein as a patient monitoring device or patient monitoringsystem 200. The hub includes a display 224, and a docking station 226,which can be configured to mechanically and electrically mate with theportable patient monitoring device 100, each housed in a movable,mountable and portable housing 228. The housing 228 includes a generallyupright inclined shape configured to rest on a horizontal flat surface,although the housing 228 can be affixed in a wide variety of positionsand mountings and include a wide variety of shapes and sizes.

The display 224 may present a wide variety of measurement and/ortreatment data in numerical, graphical, waveform, or other displayindicia 232. The display 224 can occupy much of a front face of thehousing 228; although an artisan will appreciate the display 224 mayinclude a tablet or tabletop horizontal configuration, a laptop-likeconfiguration or the like. Other examples may include communicatingdisplay information and data to a table computer, smartphone,television, or any display system recognizable to an artisan. Theupright inclined configuration of FIG. 2A presents display informationto a caregiver in an easily viewable manner. The patient monitoringdevice 200 may display information for a variety of physiologicalparameters, such as but not limited to oxygen saturation (SpO2),hemoglobin (Hb), oxyhemoglobin (HbO2), total hemoglobin,carboxyhemoglobin, methemoglobin, perfusion index (Pi), pulse rate (PR)of blood pressure, temperature, electrocardiogram (ECG), motion data,accelerometer data, respiration, continuous blood pressure, plethvariability index (PVI), oxygen content, oxygen reserve index, acousticrespiration rate (RRa), respiration rate from the pleth, cardiac output,stroke volume, and/or fluid responsiveness.

FIG. 2B illustrates a simplified example hardware block diagram of thepatient monitoring device 200. As shown in FIG. 2B, the housing 228 ofthe patient monitoring device 200 positions and/or encompasses aninstrument board 202, a core or technical board 212, the display 224,memory 204, and the various communication connections, including serialports 230, channel ports 222, Ethernet ports 205, nurse call port 206,other communication ports 208 including standard USB, or the like, and adocking station interface 210. The instrument board 202 can include oneor more substrates including communication interconnects, wiring, portsand the like to enable the communications and functions describedherein, including inter-board communications. The technical board 212includes the main parameter, signal, and other processor(s) and memory.A portable monitor board (“RIB”) 214 includes patient electricalisolation for the monitor 100 and one or more processors. A channelboard (“MID”) 216 controls the communication with the channel ports 222including optional patient electrical isolation and power supply 218,and a radio board 220 includes components configured for wirelesscommunications.

Additionally, the instrument board 202 and/or the technical board 212may advantageously include one or more processors and controllers,busses, all manner of communication connectivity and electronics,memory, memory readers including EPROM readers, and other electronicsrecognizable to an artisan from the disclosure herein. Each board caninclude substrates for positioning and support, interconnect forcommunications, electronic components including controllers, logicdevices, hardware/software combinations and the like to accomplish thetasks designated above and others.

An artisan will recognize from the disclosure herein that the instrumentboard 202 and or the technical board 212 may include a large number ofelectronic components organized in a large number of ways.

Because of the versatility needed to process many differentphysiological parameters, the technical board 212 can further include arevision number or other indication of the circuit design andcapabilities of a specific technical board 212.

Likewise, because of the versatility needed to display the processedphysiological parameters for use by many different end users, theinstrument board 202 can further include a revision number or otherindication of the circuit design and capabilities of the specificinstrument board 202.

The memory 204 can include a user interface module 240, a signalprocessing module 242, instrument configuration parameters 244, andlocal configuration parameters 246.

The instrument board 202 can access the user interface module 240 toprocess the waveforms, alerts, and alarms to provide indications of thewaveforms, alerts, alarms or other data associated with thephysiological parameters for the patient monitoring device 200. Thetechnical board 212 can access the signal processing module 242 toprocess the physiological information for the patient monitoring device200.

Software for the patient monitoring device 200 is also subject toupgrading to increase its capabilities. The signal processing module 242can further include a version number or other indication of the codefound in the specific signal processing module 242. Likewise, the userinterface module 240 can further include a version number or otherindication of the code found on the specific user interface module 240.

Some or all of the serial numbers, the model numbers, and the revisionnumbers of the technical board 212 and the instrument board 202 thatinclude the specific patient medical monitoring hub 150 can be stored inthe instrument configuration parameters 244. Further, the versionnumbers of the signal processing module 242 and the user interfacemodule 240 can be stored in the instrument configuration parameters 244.The instrument configuration parameters 244 further include indicationsof the physiological parameters that are enabled, and indications of thephysiological parameters that are capable of being enabled for thepatient monitoring device 200.

The local configuration parameters 246 can include a location of thepatient monitoring device 200 within the facility, an indication ofwhether the device is configured for adult or pediatric monitoring, andthe like.

The patient monitoring device 200 can include a Root® Patient Monitoringand Connectivity Platform by Masimo Corporation, Irvine, Calif. thatincludes the Radical-7® also by Masimo Corporation, Irvine, Calif.

FIG. 3 illustrates an example perspective view of the back of thepatient monitoring device 200 of FIG. 2A, showing an example serial datainputs. The inputs can include RJ 45 ports. As is understood in the art,these ports include data ports similar to those found on computers,network routers, switches and hubs. A plurality of these ports can beused to associate data from various devices with the specific patientidentified in the patient monitoring device 200. FIG. 3 also shows aspeaker, the nurse call connector, the Ethernet connector, the USBs, apower connector and a medical grounding lug.

Patient Hydration

Dehydration is a condition that can occur when the loss of body fluids,mostly water, exceeds the amount that is taken in. For example, the bodyis constantly losing fluids through breathing, sweat loss, and urinaryexcretion. In addition, the body can lose fluids as a result ofpreoperative fasting, surgical blood loss, fluid shifts or otherpathologic processes. With dehydration, more water is moving out ofindividual cells and then out of the body than the amount of water thatis taken in. Medically, dehydration usually means a person has lostenough fluid so that the body begins to lose its ability to functionnormally.

The severity of dehydration can vary based on the amount of fluids inthe patient's body. For example, in some cases, dehydration can beclassified based on levels or a degree of dehydration. For instance, insome cases, if a patient is dehydrated, a level of the patient'sdehydration can be classified as one of mild dehydration, moderatedehydration, or severe dehydration, or somewhere in between. In somecases, mild dehydration corresponds to a 3% to 5% drop in fluids ascompared to normal or average fluid levels of the patient, moderatedehydration corresponds to a 6% to 10% drop in fluids as compared tonormal or average fluid levels of the patient, and severe dehydrationcorresponds to more than a 10% drop in fluids as compared to normal oraverage fluid levels of the patient. However, it will be understood thatthe range or categorizations of degrees of dehydration can vary acrossembodiments. For example, in some cases, patient hydration can bebinary: dehydrated or not dehydrated. Furthermore, in some cases,patient hydration can correspond to a sliding scale, such as a scalefrom 0 to 100. Further still, the ranges or categorizations of degreesof dehydration can vary based on a patient's age, gender, weight, etc.

Dehydration can itself be dangerous. Furthermore, dehydration can causecommon conditions including, but not limited to, constipation, falls,urinary tract infections, pressure ulcers, malnutrition, incontinence,confusion, acute kidney injury, cardiac disease or venousthromboembolism. For some patients, preventing or treating dehydrationis difficult without assistance. For instance, a patient may not be ableto drink or consume fluids. In some such cases, fluids can beadministered to the patient, for example, intravenously. However, inmany instances, dehydrated can be difficult to detect or predict.Accordingly, it can be desirable to gage an accurate assessment ofpatient hydration or dehydration.

In some cases, the system can obtain an accurate assessment of patienthydration or dehydration (non-limiting example, whether a hydrationthreshold is satisfied or not satisfied) using physiological data of thepatient. For example, the system can include (or receive signals from) apulse oximeter, which can be positioned on the patient. In some cases,the pulse oximeter can detect a pleth signal, and can communicate thepleth signal, or an indication thereof, to the system.

FIG. 4 illustrates a pleth signal 400 plotted on an intensity axis 401versus a time axis 402. The pleth signal 400 has multiple pulses 410,which correspond to pulsatile blood flowing within a tissue site. Asillustrated, each pulse 410 is characterized by a plurality of featuressuch as a peak amplitude 412, valley amplitude 414, and period 416.Further, pleth signal 400 defines a pleth envelope 450 interpolated frompulse peaks 412 and pulse valleys 414.

Perfusion values, or a perfusion index (PI), can be defined for eachpulse 410. PI generally reflects the amplitude of the waveform and iscalculated as the pulsatile infrared signal (AC 420 or variablecomponent), indexed against the non-pulsatile infrared signal (DC 430 orconstant component). PI can be expressed as a percentage (for example,0.02-20%). In some cases, PI is the ratio of the pulsing blood tonon-pulsing blood flow, and can be determined using the followingequation:

$\begin{matrix}{{PI} = \frac{A\; C}{D\; C}} & ( {{Equation}\mspace{14mu} 1} )\end{matrix}$

where AC can represent a peak amplitude 412 minus a valley amplitude 414for a particular pulse, and DC can represent a peak amplitude 412 for aparticular pulse. Among other things, PI can be used to indicate astrength of blood flow a measurement site. In some cases, DC canrepresent a value other than peak amplitude 412, such as a valleyamplitude 414 or an average of peak amplitude 412 and valley amplitude414, to name a few.

In some cases, a patient monitoring device, such as the patientmonitoring device 100 of FIG. 1, can identify a pleth variabilityparameter that is responsive to variations of the pleth. In some cases,a pleth variability parameter is a clinically useful hemodynamicmeasurement because it can respond to changes in patient physiology,thereby acting as a useful indicator of various physiological conditionsor the efficacy of treatment for those conditions. Advantageously, plethvariability measures may provide a numerical indication of a person'sphysical condition or health. For example, changes in a plethvariability parameter may be representative of changes in physiologicfactors such as patient hydration.

One variability measure is a Pleth Variability Index (PVI or PVi®)(developed by Masimo® Corporation, Irvine, Calif., USA)) as described ingreater detail in U.S. Pub. No. 2008/0188760, filed Dec. 7, 2007, andentitled “PLETHYSMOGRAPH VARIABILITY PROCESSOR,” which is herebyincorporated by reference herein in its entirety.

PVI can be based on perfusion index (PI) variations during a respiratorycycle. For example, PVI can be a measure of dynamic changes in PI thatoccur during one or more complete respiratory cycles. As illustratedfrom Equation 2 below, the calculation for PVI can be accomplished bymeasuring changes in PI over a time interval where one or more completerespiratory cycles have occurred, and can be determined using thefollowing equation:

$\begin{matrix}{{PVI} = {\frac{{PI}_{m\; {ax}} - {PI}_{m\; i\; n}}{{PI}_{m\; {ax}}}*100}} & ( {{Equation}\mspace{14mu} 2} )\end{matrix}$

In some cases, PVI can be automatically or continuously calculated andcan represent respiratory variations in the plethysmographic waveform.Furthermore, in some cases, PVI may be indicative of or correlated withpatient hydration or dehydration. As a non-limiting example, in somecases, a relatively lower PVI can indicate that the patient's hydrationlevel does not satisfy a hydration threshold (e.g., the patient isdehydrated). As a corollary, a relatively high PVI can indicate that thepatient's hydration level satisfies a hydration threshold (e.g., thepatient is not dehydrated). However, it will be understood that, in somecases, a relatively low PVI can indicate that the patient's hydrationlevel satisfies a hydration threshold and/or a relatively high PVI canindicate that the patient's hydration level does not satisfy a hydrationthreshold. In some cases, PVI can be displayed as a percentage(numerical value) and/or a trend graph. Similarly, the patientmonitoring device can display (or cause a display to display) anindication of the patient's hydration status (for example, dehydrated,hydrated, no dehydrated, mildly dehydration, moderately dehydration, orseverely dehydration mild dehydration, etc.) based at least in part onPVI. As another example, in some cases, the patient monitoring devicecan provide an indication to (or control a device to) initiateadministration of fluids, continue administration of fluids, orterminate administration of fluids based at least in part on PVI. Forexample, in some cases, based on a determination that the patient isdehydrated, the patient monitoring device can provide an indication to(or control a device to) initiate administration of fluids or continueadministration of fluids. As a corollary, in some cases, based on adetermination that the patient is not dehydrated, the patient monitoringdevice can provide an indication to (or control a device to) terminateadministration of fluids.

Cardiac Output

Cardiac output can refer to an amount or volume of blood that the heartpumps through the circulatory system, and is generally expressed inliters per minute. Sufficient cardiac output (that is, a cardiac outputthat satisfies a threshold cardiac output) helps keep blood pressure atthe levels needed to supply oxygen-rich blood to the brain and othervital organs. In some cases, cardiac output can be calculated using thefollowing equation:

CO=HR×SV  (Equation 3)

where CO is the Cardiac output, HR is heart rate (e.g., the number ofheart beats per minute (bpm)), and SV is stroke volume (e.g., the amountof blood pumped from the left (or right) ventricle of the heart in onecontraction). Accordingly, the cardiac output can be a function of heartrate and stroke volume, and thus, in some cases, the factors affectingstroke volume or heart rate may also affect cardiac output.

As a non-limiting example, for someone weighing about 70 kg (154 lbs.),a healthy heart with a normal cardiac output can pump about 5 to 6liters of blood every minute when a person is resting. During exercise,the body may need three or four times its normal cardiac output, becausethe muscles need more oxygen. Thus, during exercise, the heart typicallybeats faster (known as increased heart rate) so that more blood flowsout to the body. The heart can also increase its stroke volume bypumping more forcefully or increasing the amount of blood that fills theleft ventricle before it pumps. Generally, an increase in cardiac outputcan be favorable or desired, as it can indicate an increase in thesupply of oxygen-rich blood. In contrast, a decrease in cardiac outputcan be unfavorable or not desired, as it can indicate a decrease in thesupply of oxygen-rich blood.

Fluid Responsiveness

Volume expansion can be applied to increase an amount of fluid presentin a patient's body, and is frequently used before, during, or aftersurgery to correct dehydration or fluid deficits created by, forexample, preoperative fasting, surgical blood loss, sweat loss, urinaryexcretion, fluid shifts or other pathologic processes. Techniques forvolume expansion include, among other methods, oral rehydration therapy(for example, drinking), intravenous therapy (for example, deliveringliquid substances directly into a vein), rectal therapy (for example,with a Murphy drip), or by hypodermoclysis (for example, the directinjection of fluid into the subcutaneous tissue).

In general, the objective of volume expansion is to improve oxygendelivery or overall hemodynamic function. However, some patients may notrespond to volume expansion with improved oxygen delivery or improvedoverall hemodynamic function. For example, these patients may notrespond to the volume expansion with an increase in stroke volume orcardiac output. In these patients, volume expansion can be eitherineffective or deleterious, and can result in worsening oxygen delivery,inducing systemic and pulmonary edema or, in some cases, cardiacfailure. In some cases, patients that do not respond to volume expansionwith improved oxygen delivery or improved overall hemodynamic functionare referred to as being fluid unresponsive. In some cases, patientsthat do respond to volume expansion with improved oxygen delivery orimproved overall hemodynamic function are referred to as being fluidresponsive. Thus, in some cases, a patient can be categorized as fluidunresponsive or fluid responsive based on how he or she will respond tovolume expansion (sometimes referred to as a patient's fluidresponsiveness).

As described herein, some patient's may be fluid unresponsive. Thus, itcan be important to determine or predict a patient's fluidresponsiveness (e.g. how a patient will respond to volume expansion)prior to administering fluids. In other words, prior to fluidadministration, it can be important to determine or predict a patient'sfluid responsiveness (or how fluid administration will affect apatient's cardiac output). A patient identified as someone that willrespond to volume expansion with an increase in cardiac output such thatthe cardiac output satisfies a threshold cardiac output (or that theincrease in cardiac output satisfies a threshold increase in cardiacoutput) can be classified as fluid responsive. In contrast, a patientidentified as someone that will not respond to volume expansion with acardiac output that satisfies a threshold cardiac output can beclassified as fluid unresponsive. In some cases, an indication of apatient's fluid responsiveness can include an indication that thepatient is fluid responsive, fluid unresponsive, or somewhere inbetween.

Although some static and dynamic cardiopulmonary indices have been usedto predict fluid responsiveness, many of these measures generally havelow predictive value, or can risk fluid overload (the condition ofhaving too much fluid in the body, or the state of one of the chambersof the heart in which too large a volume of blood exists within it forit to function efficiently). For example, a fluid challenge can includeadministering fluids to patients in order to assess their response tofluid therapy and guide further treatment decisions. By administering asmall amount of fluid in a short period of time, the clinician canassess the patient's fluid responsiveness. However, because volumeexpansion includes administering fluid to the patient, a fluid challengecan risk fluid overload.

Passive Leg Raising (PLR) Test

In some cases, the system can utilize information obtained as a resultof the patient performing or being administered a passive leg raising(PLR) test to determine the patient's fluid responsiveness. The PLR testcan vary across embodiments, but is generally a non-invasive, bedsidetest that involves elevating a patient's legs, and can be used toevaluate whether a patient will benefit from volume expansion. In somecases, the PLR test can be used to determine whether cardiac outputrespond such that it satisfies or does not satisfy a cardiac outputthreshold as a result of volume expansion.

In general, the PLR test involves raising the legs of a patient (withouther active participation), which causes gravity to pull blood from thelegs, thus increasing circulatory volume available to the heart,sometimes known as cardiac preload. The PLR test can be performed withthe patient's active participation. For instance, the patient canactively raise his or legs. The PLR test can be performed with thepatient's active participation. By transferring a volume of blood (forexample, around 300 mL) from the lower body toward the heart, PLR mimicsa fluid challenge. However, no fluid is infused and the hemodynamiceffects are rapidly reversible, thereby avoiding the risks of fluidoverload.

A method for performing a PLR test can include a sequence of steps. Forexample, the PLR test generally includes some combination of thefollowing steps: (1) placing the patient in a semi-recumbent position(the patient's head and torso are positioned upright at an angle ofabout 45° relative to the patient's legs, which are resting flat on thetable); (2) assessing the cardiac output. Here, the patient's heartrate, stroke volume, or the like can be identified by the system, orcardiac output can be determined; (3) moving the patient to a recumbentposition (the patient's legs are raised and torso is lowered, where,ultimately, the patient is lying on her back with her feet raised at anangle of about 45°. Here, it may be beneficial not to have the patientselevate her legs manually because it may provoke pain, discomfort, orawakening that can cause adrenergic stimulation, giving false readingsof cardiac output by increasing heart rate); (4) re-assessing thecardiac output. Here, the patient's heart rate, stroke volume, or thelike can be identified by the system, or cardiac output can bedetermined; (5) returning the patient to a semi-recumbent position; and(6) re-assessing the cardiac output. Here, the patient's heart rate,stroke volume, or the like can be identified by the system, or cardiacoutput can be determined.

In general, the PLR test can be can used to assess fluid responsivenesswithout any fluid challenge, where the latter can lead to fluidoverload. The real-time effects of the PLR test on hemodynamicparameters such as blood pressure, heart rate, or cardiac output can beused to guide the assessments on the patient's fluid responsiveness. Forexample, in some cases, if the patient's cardiac output responds suchthat it satisfies a threshold cardiac output, then it can be determinedthat the patient is fluid responsive. In contrast, in some cases, if thepatient's cardiac output responds such that it does not satisfy athreshold cardiac output, then it can be determined that the patient isfluid unresponsive.

Flow Diagrams

FIG. 5 is a flow diagram illustrative of an embodiment of a routine 500,implemented by a processor, for assessing or predicting fluidresponsiveness. One skilled in the relevant art will appreciate that theelements outlined for routine 500 can be implemented by one or morecomputing devices that are associated with the system 200, such as theprocessor 104 or the monitoring device 100. Accordingly, routine 500 hasbeen logically associated as being generally performed by the processor104 of FIG. 1. However, the following illustrative embodiment should notbe construed as limiting. Furthermore, it will be understood that thevarious blocks described herein with reference to FIG. 5 can beimplemented in a variety of orders. For example, the processor 104 canimplement some blocks concurrently or change the order, as desired.Furthermore, it will be understood that fewer, more, or different blockscan be used as part of the routine 500.

At block 502, the processor 104 receives a sensor signal correspondingto a non-invasive physiological sensor. As described herein, thenon-invasive physiological sensor, such as sensor 102 of FIG. 1, caninclude at least one emitter configured to emit light at one or morewavelengths. Further, the non-invasive sensor can include a detectorconfigured to detect the light from the least one emitter after thelight has interacted with the tissue site of a patient, and generate thesensor signal based at least in part on the detected light. For example,the non-invasive physiological sensor can be attached to the patient,such as to the patient's finger.

At block 504, the processor 104 determines a plethysmograph variabilityparameter based at least in part on the sensor signal. In some cases,the plethysmograph variability parameter can includes a value thatrelates or quantifies changes in patient physiology. For example, insome cases, the plethysmograph variability parameter can reflectvariations that occur during the respiratory cycle or changes inphysiologic factors such as changes in fluid responsiveness, volemia,ventricular preload, etc.

The plethysmograph variability parameter can be determined using one ormore of various techniques, such as any one or more of the techniquesdisclosed in U.S. Patent Publication No. 2013/0296713, filed Apr. 8,2013, which is hereby incorporated by reference in its entirety. Forexample, the processor 104 can determine perfusion values, or aperfusion index (PI), from pulses of a plethysmograph waveform thatcorresponds to the sensor signal. Furthermore, the processor 104 candetermine the plethysmograph variability parameter based on theperfusion values or the PI. For instance, the determination of theplethysmograph variability parameter can include calculating adifference between perfusion values and normalizing the difference. Insome cases, the plethysmograph variability parameter corresponds to oneor more plethysmograph variability index (PVI) values. For example, aPVI value can be a measure of the dynamic changes in the Perfusion Index(PI) that occur during one or more complete respiratory cycles.

At block 506, the processor 104 determines a prediction of fluidresponsiveness or unresponsiveness based at least in part on theplethysmograph variability parameter. For example, in some cases, theplethysmograph variability parameter includes a numerical value. In somesuch cases, a relatively higher plethysmograph variability parameter mayindicate fluid responsiveness. For example, a higher plethysmographvariability parameter may indicate more variance in the perfusion valuesand a greater likelihood that the patient will respond to fluidadministration with an increase in cardiac output. As a corollary, insome such cases, a relatively lower plethysmograph variability parametermay indicate fluid unresponsiveness. For example, a lower plethysmographvariability parameter may indicate less variance in the perfusion valuesand therefore a lower likelihood that the patient will respond to fluidadministration with an increase in cardiac output.

In some cases, the processor 104 can further determine a confidencevalue associated with the prediction of fluid responsiveness orunresponsiveness. For example, in some cases, the confidence in aprediction of fluid responsiveness increases (i.e., a higher confidence)as the plethysmograph variability parameter increases and decreases(i.e., a lower confidence) as the plethysmograph variability parameterdecreases. As a corollary, in some cases, the confidence in a predictionof fluid unresponsiveness increases as the plethysmograph variabilityparameter decreases and decreases as the plethysmograph variabilityparameter increases.

At block 508, the processor 104 determines a prediction of fluidresponsiveness or unresponsiveness based at least in part on a fluidresponsiveness parameter that is associated with an elevation of one ormore limbs of the patient. For example, in some cases, some variance ofa passive leg raise (PLR) test can be performed on the patient. Asdescribed herein, a PLR test is a non-invasive, bedside test, which canresults in the elevation of one or more limbs (e.g., one or more legs)of the patient.

In some cases, the PLR test can be automated or semi-automated. Forexample, the processor 104 can cause the PLR test to begin, for instanceby controlling movement of a patient's bed. In some cases, the PLR testcan be performed manually, such as by a physician. In some cases, theprocessor 104 can provide an instruction to perform the PLR test. Theinstruction can include an auditory, visual or other indication. In somecases, the processor 104 can provide instructions throughout the PLRtest. For example, the processor 104 can generate a graphical userinterface (GUI) that displays a graphical indication of one or moresteps of the PLR test. In some cases, the processor 104 can cause adisplay (for example, display 106 or 224) to display a visualwalkthrough of the steps of the PLR test. FIGS. 6A-6C illustrate anembodiment of an example GUI that displays example graphics forinstructing or implementing the PLR test on a patient. As illustrated,for one or more steps of the PLR test, the GUI can show a graphicaldepiction of the orientation of the patient and/or the patient's bed. Inaddition or alternatively, the GUI can include instructions for thecaregiver, such as an indication of when to obtain results from the PLRtest, a timer or alarm for a particular step, or the like.

The fluid responsiveness parameter can vary across embodiments. Forexample, in some cases, the fluid responsiveness parameter includes ameasure of cardiac output. As another example, in some cases, the fluidresponsiveness parameter includes a measure of heart rate. As anotherexample, in some cases, the fluid responsiveness parameter includes ameasure of stroke volume. The fluid responsiveness parameter can bedetermined at one or more of various stages of the PLR test. Forexample, the fluid responsiveness parameter can be determined prior toperformance of the PLR test, during the PLR test, and/or after the PLRtest has completed. Furthermore, the fluid responsiveness parameter canbe measured in real-time by one or more sensors and/or can be calculatedby the processor 104 using sensor data. Alternatively, in some cases, aphysician and/or medical device can monitor the fluid responsivenessparameter of the patient, and the physician can enter fluidresponsiveness parameter as an input to the processor 104.

The processor 104 can determine a prediction of fluid responsiveness orunresponsiveness in various ways. For example, changes in the fluidresponsiveness parameter can be used to guide the determination of theprediction. For example, in some cases, a first fluid responsivenessparameter is measured prior to during the PLR test and a second fluidresponsiveness parameter is measured during or after PLR test. In somesuch cases, the processor 104 can determine a prediction of fluidresponsiveness or unresponsiveness based one a comparison for the firstfluid responsiveness parameter and the second fluid responsivenessparameter. For example, if the second fluid responsiveness parameterincreases (for example, by a threshold amount) relative to the firstfluid responsiveness parameter, then the processor 104 can determine aprediction of fluid responsiveness. Put another way, in some cases, ifthe PLR test causes the fluid responsiveness parameter to increase (forexample, by a threshold amount), the processor 104 can determine aprediction of fluid responsiveness. As a corollary, in some cases, ifthe PLR test causes the fluid responsiveness parameter to stay the same,decrease, or not increase by threshold amount, the processor 104 candetermine a prediction of fluid unresponsiveness.

In some cases, the processor 104 can further determine a confidencevalue associated with the prediction of fluid responsiveness orunresponsiveness. For example, in some cases, the confidence in aprediction of fluid responsiveness or unresponsiveness is based on theamount that the fluid responsiveness parameter changes over time. Forexample, for a prediction of fluid responsiveness, a relatively largerincrease in the fluid responsiveness parameter can result in a higherconfidence value, while a relatively smaller increase can result in alower confidence value. As another example, for a prediction of fluidunresponsiveness, no increase or a decreases in the fluid responsivenessparameter can result in a higher confidence value, while an increase inthe fluid responsiveness parameter can result in a lower confidencevalue.

At block 508, the processor 104 outputs an indication of an overallprediction of fluid responsiveness or fluid responsiveness. For example,the processor 104 can determine the overall prediction of fluidresponsiveness or fluid responsiveness based at least in part on thedeterminations at block 506 and/or block 508. For example, the overallprediction of fluid responsiveness or fluid responsiveness can be basedat least in part on one or more of the prediction of fluidresponsiveness or unresponsiveness using the plethysmograph variabilityparameter, the prediction of fluid responsiveness or unresponsivenessusing the fluid responsiveness parameter, and/or confidence valuesassociated therewith.

As an example, if both blocks 506 and 508 return a prediction of fluidresponsiveness, then the processor 104 can output an indication of fluidresponsiveness. As an example, if both blocks 506 and 508 return aprediction of fluid unresponsiveness, then the processor 104 can outputan indication of fluid unresponsiveness. In some cases, if one of blocks506 and 508 returns a prediction of fluid unresponsiveness and one ofblocks 506 and 508 returns a prediction of fluid responsiveness, thenthe processor 104 can output an error code. In some cases, if one ofblocks 506 and 508 returns a prediction of fluid unresponsiveness andone of blocks 506 and 508 returns a prediction of fluid responsiveness,then the processor 104 can output the prediction of whichever methodproduced a higher confidence value, as described herein.

It will be understood that the various blocks described herein can beimplemented in a variety of orders, and that the processor 104 canimplement one or more of the blocks concurrently and/or change theorder, as desired. For example, in some cases, any of blocks 502, 504,506 and/or 508 can be implemented prior to or currently with any otherblocks 502. Furthermore, it will be understood that fewer, more, ordifferent blocks can be used as part of the routine 500. For example,the routine 500 can include blocks for controlling a device toadminister fluids to the patient or terminate administration of fluidsto the patient. For instance, in some cases, based on a prediction offluid responsiveness, the processor can cause fluid to be administeredto the patient, either by operating or controlling a medical device,such as an infusion pump, to administer fluids to the patient or byoutputting an indication to administer fluids. As another example, insome cases, based on a prediction of fluid unresponsiveness, theprocessor can cause administration of fluid to be terminated, either byoperating or controlling a medical device, such as an infusion pump, orby outputting an indication to termination administration of fluids.

Furthermore, the processor 104 can cause display on the GUI of one ormore instructions, which, when viewed, can indicate how to perform thePLR test, or a duration over which to hold a specific step of the PLRtest. Furthermore, in some cases, rather than or in addition topredicting fluid responsiveness or fluids unresponsiveness, theprocessor 104 can identify a hydration status of a patient. In somecases, if the patient is hydrated, the processor 104 doesn't initiatethe routine 500. In some cases, the processor 104 initiates the routine500 based on a determination that the patient is dehydrated.Furthermore, in some cases, the routine 500 can omit certain blocks,such as, but not limited to, blocks 502, 504, 506, and/or 508.

Terminology

The term “and/or” herein has its broadest least limiting meaning whichis the disclosure includes A alone, B alone, both A and B together, or Aor B alternatively, but does not require both A and B or require one ofA or one of B. As used herein, the phrase “at least one of” A, B, “and”C should be construed to mean a logical A or B or C, using anon-exclusive logical or.

The following description is merely illustrative in nature and is in noway intended to limit the disclosure, its application, or uses. Forpurposes of clarity, the same reference numbers will be used in thedrawings to identify similar elements. It should be understood thatsteps within a method may be executed in different order withoutaltering the principles of the present disclosure.

Features, materials, characteristics, or groups described in conjunctionwith a particular aspect, embodiment, or example are to be understood tobe applicable to any other aspect, embodiment or example describedherein unless incompatible therewith. All of the features disclosed inthis specification (including any accompanying claims, abstract anddrawings), or all of the steps of any method or process so disclosed,may be combined in any combination, except combinations where at leastsome of such features or steps are mutually exclusive. The protection isnot restricted to the details of any foregoing embodiments. Theprotection extends to any novel one, or any novel combination, of thefeatures disclosed in this specification (including any accompanyingclaims, abstract and drawings), or to any novel one, or any novelcombination, of the steps of any method or process so disclosed.

While certain embodiments have been described, these embodiments havebeen presented by way of example only, and are not intended to limit thescope of protection. Indeed, the novel methods and systems describedherein may be embodied in a variety of other forms. Furthermore, variousomissions, substitutions and changes in the form of the methods andsystems described herein may be made. Those skilled in the art willappreciate that in some embodiments, the actual steps taken in theprocesses illustrated or disclosed may differ from those shown in thefigures. Depending on the embodiment, certain of the steps describedabove may be removed, others may be added. For example, the actual stepsor order of steps taken in the disclosed processes may differ from thoseshown in the figures. Depending on the embodiment, certain of the stepsdescribed above may be removed, others may be added. For instance, thevarious components illustrated in the figures may be implemented assoftware or firmware on a processor, controller, ASIC, FPGA, ordedicated hardware. Hardware components, such as processors, ASICs,FPGAs, and the like, can include logic circuitry. Furthermore, thefeatures and attributes of the specific embodiments disclosed above maybe combined in different ways to form additional embodiments, all ofwhich fall within the scope of the present disclosure.

User interface screens illustrated and described herein can includeadditional or alternative components. These components can includemenus, lists, buttons, text boxes, labels, radio buttons, scroll bars,sliders, checkboxes, combo boxes, status bars, dialog boxes, windows,and the like. User interface screens can include additional oralternative information. Components can be arranged, grouped, displayedin any suitable order.

Although the present disclosure includes certain embodiments, examplesand applications, it will be understood by those skilled in the art thatthe present disclosure extends beyond the specifically disclosedembodiments to other alternative embodiments or uses and obviousmodifications and equivalents thereof, including embodiments which donot provide all of the features and advantages set forth herein.Accordingly, the scope of the present disclosure is not intended to belimited by the specific disclosures of preferred embodiments herein, andmay be defined by claims as presented herein or as presented in thefuture.

Conditional language, such as “can,” “could,” “might,” or “may,” unlessspecifically stated otherwise, or otherwise understood within thecontext as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements, or steps. Thus, such conditional language is notgenerally intended to imply that features, elements, or steps are in anyway required for one or more embodiments or that one or more embodimentsnecessarily include logic for deciding, with or without user input orprompting, whether these features, elements, or steps are included orare to be performed in any particular embodiment. The terms“comprising,” “including,” “having,” and the like are synonymous and areused inclusively, in an open-ended fashion, and do not excludeadditional elements, features, acts, operations, and so forth. Also, theterm “or” is used in its inclusive sense (and not in its exclusivesense) so that when used, for example, to connect a list of elements,the term “or” means one, some, or all of the elements in the list.Further, the term “each,” as used herein, in addition to having itsordinary meaning, can mean any subset of a set of elements to which theterm “each” is applied.

Conjunctive language such as the phrase “at least one of X, Y, and Z,”unless specifically stated otherwise, is otherwise understood with thecontext as used in general to convey that an item, term, etc. may beeither X, Y, or Z. Thus, such conjunctive language is not generallyintended to imply that certain embodiments require the presence of atleast one of X, at least one of Y, and at least one of Z.

Language of degree used herein, such as the terms “approximately,”“about,” “generally,” and “substantially” as used herein represent avalue, amount, or characteristic close to the stated value, amount, orcharacteristic that still performs a desired function or achieves adesired result. For example, the terms “approximately”, “about”,“generally,” and “substantially” may refer to an amount that is withinless than 10% of, within less than 5% of, within less than 1% of, withinless than 0.1% of, and within less than 0.01% of the stated amount. Asanother example, in certain embodiments, the terms “generally parallel”and “substantially parallel” refer to a value, amount, or characteristicthat departs from exactly parallel by less than or equal to 15 degrees,10 degrees, 5 degrees, 3 degrees, 1 degree, or 0.1 degree.

The scope of the present disclosure is not intended to be limited by thespecific disclosures of preferred embodiments in this section orelsewhere in this specification, and may be defined by claims aspresented in this section or elsewhere in this specification or aspresented in the future. The language of the claims is to be interpretedbroadly based on the language employed in the claims and not limited tothe examples described in the present specification or during theprosecution of the application, which examples are to be construed asnon-exclusive.

What is claimed is:
 1. A method of determining fluid responsiveness of apatient, the method comprising, with a processor comprising computinghardware: receiving a sensor signal corresponding to a non-invasivephysiological sensor, wherein the non-invasive physiological sensor isconfigured to emit light towards a tissue site of a patient, detect thelight after it has interacted with the tissue site, and generate thesensor signal based at least in part on the detected light; demodulatingthe sensor signal to generate a plethysmograph waveform comprising aplurality of pulses corresponding to pulsatile blood flow within thetissue site; determining a plethysmograph variability parameterassociated with the plethysmograph waveform, wherein the plethysmographvariability parameter quantifies variations in the plethysmographwaveform; determining a first prediction of fluid responsiveness basedat least in part on the plethysmograph variability parameter;determining a second prediction of fluid responsiveness based at leastin part on a fluid responsiveness parameter that is associated with anelevation of one or more limbs of the patient; and outputting anindication of fluid responsiveness of the patient based at least in parton the first prediction of fluid responsiveness and the secondprediction of fluid responsiveness.
 2. The method of claim 1, whereinthe plethysmograph variability parameter corresponds to a valueassociated with a pleth variability index (PVI).
 3. The method of claim1, wherein the fluid responsiveness parameter comprises a measure of atleast one of cardiac output, heart rate, or stroke volume.
 4. The methodof claim 1, further comprising: determining a plurality of perfusionparameters based at least in part on the plethysmograph waveform,wherein a particular perfusion parameter of the plurality of perfusionparameters is determined based at least in part on a peak amplitude anda valley amplitude of a corresponding pulse of the plurality of pulses;wherein said determining the plethysmograph variability parameter isbased at least in part on a difference between a first perfusionparameter and a second perfusion parameter of the plurality of perfusionparameters relative to the first perfusion parameter of the plurality ofperfusion parameters.
 5. The method of claim 1, wherein the method isperformed prior to administration fluids to the patient.
 6. The methodof claim 1, wherein the method is performed during administration fluidsto the patient.
 7. The method of claim 1, wherein the elevation of theone or more limbs of the patient is associated with a passive legraising (PLR) test.
 8. The method of claim 7, wherein the PLR test isperformed prior to administration of fluids to the patient.
 9. Themethod of claim 7, wherein the PLR test is performed duringadministration of fluids to the patient.
 10. The method of claim 1,further comprising performing an action based at least in part on theindication of the fluid responsiveness, wherein the action comprises atleast one of initiating administration of fluids to the patient,terminating the administration of the fluids to the patient, causing adisplay to display an indication of a recommendation for fluidadministration, or causing the display to display an indication of arecommendation for termination of fluid administration.
 11. The methodof claim 1, wherein the indication of fluid responsiveness indicates aresponse of stroke volume of the patient to fluid administration. 12.The method of claim 1, further comprising: determining a firstconfidence parameter corresponding to the first prediction of fluidresponsiveness; and determining a second confidence parametercorresponding to the second prediction of fluid responsiveness, andwherein the fluid responsiveness of the patient is further based atleast in part on the first confidence parameter and the secondconfidence parameter.
 13. A patient monitoring device for determiningfluid responsiveness of a patient, the patient monitoring devicecomprising: a sensor interface configured to receive a sensor signalfrom a non-invasive physiological sensor, wherein the non-invasivephysiological sensor is configured to emit light towards a tissue siteof a patient, detect the light after it has interacted with the tissuesite, and generate the sensor signal based at least in part on thedetected light; and a processor in communication with the sensorinterface and configured to: determine a plethysmograph variabilityparameter associated with a plethysmograph waveform corresponding to thesensor signal, wherein the plethysmograph waveform comprises a pluralityof pulses corresponding to pulsatile blood flow within the tissue site,wherein the plethysmograph variability parameter quantifies variationsin the plethysmograph waveform, determine a first prediction of fluidresponsiveness based at least in part on the plethysmograph variabilityparameter, determine a second prediction of fluid responsiveness basedat least in part on a fluid responsiveness parameter that is associatedwith an elevation of one or more limbs of the patient, and output anindication of fluid responsiveness of the patient based at least in parton the first prediction of fluid responsiveness and the secondprediction of fluid responsiveness.
 14. The patient monitoring device ofclaim 13, wherein the plethysmograph variability parameter correspondsto a value associated with a pleth variability index (PVI).
 15. Thepatient monitoring device of claim 13, wherein the fluid responsivenessparameter comprises a measure of at least one of cardiac output, heartrate, or stroke volume.
 16. The patient monitoring device of claim 13,wherein the elevation of the one or more limbs of the patient isassociated with a passive leg raising (PLR) test.
 17. The patientmonitoring device of claim 18, wherein the PLR test is performed priorto administration of fluids to the patient.
 18. The patient monitoringdevice of claim 18, wherein the PLR test is performed duringadministration of fluids to the patient.
 19. The patient monitoringdevice of claim 13, wherein the processor is further configured to causean action based on the fluid responsiveness of the patient, wherein theaction comprises at least one of initiating administration of fluids tothe patient, terminating the administration of the fluids to thepatient, causing a display to display an indication of a recommendationfor fluid administration, or causing the display to display anindication of a recommendation for termination of fluid administration.20. The patient monitoring device of claim 13, wherein the processor isfurther configured to: determine a first confidence parametercorresponding to the first prediction of fluid responsiveness; anddetermine a second confidence parameter corresponding to the secondprediction of fluid responsiveness, and wherein the fluid responsivenessof the patient is further based at least in part on the first confidenceparameter and the second confidence parameter.